MGMT2263
Worksheet #2
1)
For
the following scenarios, state whether the samples are dependent or
independent.
a)
Two
colleges wanted to compare the mean SAT scores on their incoming freshmen. One college
gathered 98 scores and the other took a sample of 52 scores.
b)
A
retail store would like to compare sales from two different arrangements of
displaying its merchandise. Sales are recorded for a 30-day period with one
arrangement and then sales are recorded for another 30-day period for the
alternative arrangement.
c)
Fifty
people were randomly selected to rate Coke and Pepsi on a scale from 1 to 10
and the ratings were compared.
(a and b: independent,
c: dependent)
2)
For
each of the following scenarios state which test to conduct. Choose from
Z-test, t-test assuming equal variances, t-test assuming unequal variances,
paired t-test, Wilcoxon rank-sum test or Wilcoxon signed-ranks test.
a)
A
survey is conducted in Calgary and Edmonton to see if there is any significant
difference in the average amount people spend eating out. They pull equal
sample sizes of 200 for each city.
b)
A
teacher wanted to compare marks between her two classes. She has 25 students in
one class and 28 in the other. When she checked to see if the data was normally
distributed, she found that the marks for both classes were heavily skewed
left.
c)
A
store did a shopper-intercept survey in a mall asking 100 people to rate 2 new
logos on a scale from 1 to 5, 5 being best.
d)
A
store wanted to compare average daily sales at 2 of its locations. They took
samples of 10 daily sales from both stores (the dates were independently chosen
for each store). Analysis indicated the standard deviations were equal and that
the data followed a normal distribution.
e)
A
store ran an identical ad campaign at 2 of its locations. It then sampled the
same 10 days of data from both stores in order to compare average sales between
the stores. Analysis indicated the data followed a normal distribution.
(a: Z test; b: Wilcoxon rank sum; c: Wilcoxon
signed rank; d: t-test assuming equal variances; e: paired t-test)
3)
A
video chain had to choose between 2 locations for its new store. It decided to
base its decision on the average number of videos per month watched per
household. It surveyed 100 households in the neighbourhood
of each location. The results were:
|
Mean |
Std. Dec. |
|
|
Location A |
4.4 |
1.6 |
|
Location B |
5.6 |
2.3 |
Do the residents in location B watch
significantly more videos than those in location A on average?
Test at a 5% level of significance. (Z = 4.28; residents in location B watch
more videos on average)
4)
Is
there a level of significance between 1% and 10% in which the opposite verdict
would have been reached? (p-value = 0; the answer is no)
5)
Construct
a 95% confidence interval of the difference between location B and location A.
(0.65 < mB - mA < 1.75)
6)
Suppose
they wanted to test the hypothesis that the difference in the average number of
videos rented per month between the residents in location B and those in
Location A is more than 1 per month. What would the conclusion be? (Z = 0.7138;
conclude the difference is not more than 1 per month)
7)
A
researcher wanted to determine if there is any significant difference between
executives and regular workers in the average number of hours spent tending to
emails, text messages, etc. For a random sample of 150 executives, the average
per week was 13.5 hours with a standard deviation of 2.4 hours. For a random sample of 200
regular workers, the average per week was 11.5 hours with a standard deviation
of 4.5 hours. Test at a 5% level of significance. (Z = 5.35; conclude there is
a significant difference)
8)
Construct
a 95% confidence interval in the average difference between executives and
regular workers in the average time on email, etc., converting the limits to
the nearest minute. Interpret the interval. If this interval were used to test
the hypothesis in question 7, why would the same conclusion be
reached?
(76 < m1 - m2 < 164; hypothesis difference of
zero lies outside the interval)
9)
Suppose
a level of significance had not been chosen for the hypothesis in question 7.
Why would the same conclusion be reached? (p-value
< 1%)
10)
What
would be the appropriate one-tail test? What would be the conclusion? (executives
spend significantly more time on email, etc. than regular workers)
From the textbook:
9.8 (page
274)
9.43 (page
289)
9.48 (page
290)